Update app.py

app.py

@@ -10,9 +10,7 @@ import numpy as np
 import PIL.Image
 import spaces
 import torch
-from diffusers import AutoencoderKL, DiffusionPipeline, DPMSolverMultistepScheduler
-
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+from diffusers import AutoencoderKL, DiffusionPipeline, EulerDiscreteScheduler
 
 DESCRIPTION = "# SDXL"
 if not torch.cuda.is_available():
@@ -63,11 +61,13 @@ def generate(
     if torch.cuda.is_available():
 
         if not use_vae:  
-            pipe = DiffusionPipeline.from_pretrained(dropdown_model, torch_dtype=torch.float16)
+            scheduler = EulerDiscreteScheduler.from_pretrained(dropdown_model, subfolder="scheduler")
+            pipe = DiffusionPipeline.from_pretrained(dropdown_model, scheduler=scheduler, torch_dtype=torch.float16)
             
         if use_vae:
+            scheduler = EulerDiscreteScheduler.from_pretrained(dropdown_model, subfolder="scheduler")
             vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16, variant="fp16")
-            pipe = DiffusionPipeline.from_pretrained(dropdown_model, vae=vae, torch_dtype=torch.float16)
+            pipe = DiffusionPipeline.from_pretrained(dropdown_model, vae=vae, scheduler=scheduler, torch_dtype=torch.float16)
             
         if use_lora:
             pipe.load_lora_weights(lora)